[1]赵骞,韩金辉,徐茂,等.基于局部对比度背景估计的红外小目标检测方法[J].智能系统学报,2022,17(2):314-324.[doi:10.11992/tis.202101009]
ZHAO Qian,HAN Jinhui,XU Mao,et al.Infrared small-target detection utilizing background estimation combined with local contrast[J].CAAI Transactions on Intelligent Systems,2022,17(2):314-324.[doi:10.11992/tis.202101009]
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ZHAO Qian,HAN Jinhui,XU Mao,et al.Infrared small-target detection utilizing background estimation combined with local contrast[J].CAAI Transactions on Intelligent Systems,2022,17(2):314-324.[doi:10.11992/tis.202101009]
基于局部对比度背景估计的红外小目标检测方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
17
期数:
2022年第2期
页码:
314-324
栏目:
学术论文—机器感知与模式识别
出版日期:
2022-03-05
- Title:
- Infrared small-target detection utilizing background estimation combined with local contrast
- Keywords:
- IR small target; max-mean; background estimation; ratio-difference joint; local contrast; target detection; single frame detection; noise-resistant ability
- 分类号:
- TP391.4
- 摘要:
- 为缓解复杂背景对红外小目标检测任务的干扰，提出一种新的红外小目标检测方法。该方法将背景估计与局部对比度相结合，以提高算法的检测性能。提出了一种更适合于小目标检测的双层均值最大化背景估计算法，以获得更准确的基准背景值。在原始图像和估计背景之间提出了比差联合局部对比度度量方法，可以在增强目标的同时抑制各种类型的复杂背景。通过实验对比分析，验证该方法的有效性和鲁棒性。
- Abstract:
- In order to alleviate the interference of complex backgrounds in infrared small target detection, a new infrared small target detection method is proposed. The new method combines background estimation with local contrast to improve the detection performance of the algorithm. The main work includes the following aspects: First, a double-layer max-mean background estimation algorithm that is more suitable for small target detection is proposed to get a more accurate background benchmark. Then, a ratio-difference joint local contrast measure is proposed between the raw image and the estimated background to enhance the different sizes of true targets while simultaneously suppressing various types of complex backgrounds. The analysis and comparison in the experiment show its effectiveness and robustness.
- 参考文献/References:
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备注/Memo
收稿日期:2021-01-08。
基金项目:国家自然科学基金项目(61802455，62003381)；河南省重点研发与推广专项(科技攻关)项目(192102210089，212102210525)
作者简介:赵骞，讲师，博士，中国人工智能学会会员，主要研究方向为模式识别与智能机器人、信息融合。主持国家自然科学基金青年项目1项，河南省重点研发与推广专项目1项。发表学术论文5篇;韩金辉，讲师，博士，主要研究方向为红外图像处理、红外弱小目标检测。主持国家自然科学基金青年项目1项，河南省重点研发与推广专项1项，河南省教育厅高等学校重点科研项目1项。发表学术论文10篇;徐茂，助教，主要研究方向为情感计算、模式识别与智能机器人
通讯作者:韩金辉.E-mail:hanjinhui@zknu.edu.cn
更新日期/Last Update:
1900-01-01